TY - JOUR
T1 - A metabolomic approach to determine the geographical origins of Anemarrhena asphodeloides by using UPLC-QTOF MS
AU - Kim, Nahyun
AU - Ryu, Seung Mok
AU - Lee, Dong Hyuk
AU - Lee, Jae Won
AU - Seo, Eun Kyoung
AU - Lee, Je Hyun
AU - Lee, Dongho
N1 - Funding Information:
This work was supported by a grant from the Korea Food and Drug Administration for Studies on Standardization of Herbal Medicine (2008) and a Korea University Grant .
PY - 2014/4/15
Y1 - 2014/4/15
N2 - An ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF MS) method was developed for metabolite profiling of Anemarrhena asphodeloides Bunge from two different geographical origins. In this study, the metabolite profile data obtained using UPLC-QTOF MS was subjected to multivariate statistical analyses, such as the principal component analysis and the hierarchical clustering analysis, to compare metabolite patterns among A. asphodeloides samples. Furthermore, a metabolite selection method known as significance analysis of microarrays (SAM) was applied to further select metabolites and to identify key constituents to efficiently distinguish between geographical origins. The UPLC-QTOF MS analysis successfully classified 21 samples into two distinct groups according to their geographical origins. The validation method used to assess the analytical stability and accuracy of these data is also described. These results suggest that this proposed method is reliable, accurate, and effective for geographic classification of A. asphodeloides, thus guiding its proper use for therapeutic purposes.
AB - An ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF MS) method was developed for metabolite profiling of Anemarrhena asphodeloides Bunge from two different geographical origins. In this study, the metabolite profile data obtained using UPLC-QTOF MS was subjected to multivariate statistical analyses, such as the principal component analysis and the hierarchical clustering analysis, to compare metabolite patterns among A. asphodeloides samples. Furthermore, a metabolite selection method known as significance analysis of microarrays (SAM) was applied to further select metabolites and to identify key constituents to efficiently distinguish between geographical origins. The UPLC-QTOF MS analysis successfully classified 21 samples into two distinct groups according to their geographical origins. The validation method used to assess the analytical stability and accuracy of these data is also described. These results suggest that this proposed method is reliable, accurate, and effective for geographic classification of A. asphodeloides, thus guiding its proper use for therapeutic purposes.
KW - Anemarrhena asphodeloides
KW - Metabolite profiling
KW - Metabolite selection
KW - Method validation
KW - UPLC-QTOF MS
UR - http://www.scopus.com/inward/record.url?scp=84893419382&partnerID=8YFLogxK
U2 - 10.1016/j.jpba.2013.12.040
DO - 10.1016/j.jpba.2013.12.040
M3 - Article
C2 - 24486682
AN - SCOPUS:84893419382
SN - 0731-7085
VL - 92
SP - 47
EP - 52
JO - Journal of Pharmaceutical and Biomedical Analysis
JF - Journal of Pharmaceutical and Biomedical Analysis
ER -